Update app.py
Browse files
app.py
CHANGED
@@ -6,7 +6,7 @@ import pandas as pd
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from transformers import pipeline
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from huggingface_hub import hf_hub_download
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# **📌 先运行 `preprocess.py
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processed_data_path = "processed_data.csv"
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if not os.path.exists(processed_data_path):
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@@ -28,11 +28,15 @@ model.load_model(model_path)
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# **📌 LLM 解析用户输入**
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def chat_with_llm(user_input):
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prompt = f"
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try:
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response = generator(prompt, max_length=
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extracted_text = response[0]['generated_text']
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return extracted_text
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except Exception as e:
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return f"❌ GPT-Neo 处理错误: {str(e)}"
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@@ -55,16 +59,26 @@ def predict_lottery(year, period, num1, num2, num3, num4, num5, num6, special):
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# **进行预测**
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prediction = model.predict(features)
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# **📌 结合 LLM 和 XGBoost**
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def predict_and_interact(user_input):
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llm_output = chat_with_llm(user_input)
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# **进行预测**
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prediction = predict_lottery(year, period, *nums, special)
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from transformers import pipeline
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from huggingface_hub import hf_hub_download
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# **📌 先运行 `preprocess.py` 处理数据**
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processed_data_path = "processed_data.csv"
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if not os.path.exists(processed_data_path):
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# **📌 LLM 解析用户输入**
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def chat_with_llm(user_input):
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prompt = f"请仅返回预测所需的参数(年份、期号、中奖号码),格式为:'年份:2025, 期号:16, 号码:[5,12,23,34,45,56], 特别号码:7'。输入问题: {user_input}"
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try:
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response = generator(prompt, max_length=50, num_return_sequences=1)
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extracted_text = response[0]['generated_text']
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# **🚀 确保 UTF-8 编码,移除特殊字符**
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extracted_text = extracted_text.encode("utf-8", "ignore").decode("utf-8").strip()
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return extracted_text
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except Exception as e:
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return f"❌ GPT-Neo 处理错误: {str(e)}"
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# **进行预测**
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prediction = model.predict(features)
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# **🚀 修正浮点数问题:四舍五入为整数**
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prediction = np.round(prediction).astype(int)
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return prediction.tolist()
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# **📌 结合 LLM 和 XGBoost**
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def predict_and_interact(user_input):
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llm_output = chat_with_llm(user_input)
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try:
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# **解析 LLM 输出格式:"年份:2025, 期号:16, 号码:[5,12,23,34,45,56], 特别号码:7"**
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parts = llm_output.split(",")
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year = int(parts[0].split(":")[1])
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period = int(parts[1].split(":")[1])
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nums = [int(x) for x in parts[2].split(":")[1].strip("[]").split()]
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special = int(parts[3].split(":")[1])
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except Exception as e:
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return f"❌ LLM 解析数据失败: {str(e)}\n\n📢 原始 LLM 解析结果: {llm_output}"
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# **进行预测**
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prediction = predict_lottery(year, period, *nums, special)
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